Year in Review: Top 6 Big Data Trends of 2014

We’ve glimpsed into the future to see where big data is headed in 2015 and beyond. Now its time to rewind the clock – just a little bit, to see how we’ve reached this point. Here’s a look at the big data trends that drove business initiatives hardest in 2014.

1. The Cloud Becomes the Launchpad

2014 saw big data and cloud computing officially hitched in a perfect pairing. Thanks to platforms like Google’s BigQuery and Cloudera, companies can fully erect massive data infrastructures in a matter of minutes, instead of the weeks or months an on-premise project would require. What’s more, the cloud offers unrivaled flexibility by providing immediate access to capacity and BI tools on a pricing model that is tailored to individual business requirements.

2. Predictive Analytics Comes Down to Earth

At one time, predictive analtyics was viewed as an advanced solution for specialized business needs. It still is to a degree, but things took a dramatic turn in 2014. Predictive analytics recently ascended to the mainstream segment of big data tools as businesses look to anticipate customer response based on past behavior and address critical issues before they become problems.

3. Social Knowledge Given Priority Status

It’s been years now since the enterprise world acknowledged what a potent weapon social media could be at strengthening awareness, marketing, and customer service endeavors. Slowly but surely, companies are coming to recognize the importance social data plays in their existing business strategies. The mix of likes, tweets, and mentions is giving organizations the intelligence needed to

better understand their audience and improve the customer experience in the process.

4. NoSQL Gets Recognition

The Hadoop platform is almost synonmous with big data itself. While Apache’s robust data management software is worthy of all the acolodes, some experts would attest that NoSQL is the true unsung hero of big data. MongoDB, Cassandra, and other NoSQL-based technologies back Hadoop by supporting gourds of unstructured data in ways that wasn’t possible with the once dominant relational database management systems like MySQL.

5. Data Tells the Story

Look around, and you’ll see marketing professionals, bloggers, and journalists across multiple fields singing the praises of storytelling. In 2014, we learned that data is one of the most powerful storytelling utensils around. Armed with the right visualization tools, savvy analysts can use data to breath life into facts that are ordinarily boring, transforming dull chunks of information into engaging, valuable insights.

6. Embedded Analytics Provide Onsite Insights

Whether it’s in the office or IT room, analyzing data is a process that has traditionally been handled behind the scenes. Analytical capabilities are increasingly being embedded into existing systems and mobile devices via apps such as Roambi. This integration has given companies in retail, production, and logistics the ability to tap into real-time insights that fuel sound business decisions on the spot.